Spatial analysis of agri-environmental policy uptake and expenditure in Scotland

Scale and context dependency of deforestation drivers: Insights from spatial econometrics in the tropics

A better understanding of deforestation drivers across countries and spatial scales is a precondition for designing efficient international policies and coherent land use planning strategies such as REDD+. However, it is so far unclear if the well-studied drivers of tropical deforestation behave similarly across nested subnational jurisdictions, which is crucial for efficient policy implementation. We selected three countries in Africa, America and Asia, which present very different tropical contexts. Making use of spatial econometrics and a multi-level approach, we conducted a set of regressions comprising 3,035 administrative units from the three countries at micro-level, plus 361 and 49 at meso- and macro-level, respectively. We included forest cover as dependent variable and seven physio-geographic and socioeconomic indicators of well-known drivers of deforestation as explanatory variables. With this, we could provide a first set of highly significant econometric models of pantropical deforestation that consider subnational units. We identified recurrent drivers across countries and scales, namely population pressure and the natural condition of land suitability for crop production. The impacts of demography on forest cover were strikingly strong across contexts, suggesting clear limitations of sectoral policy. Our findings also revealed scale and context dependencies, such as an increased heterogeneity at local scopes, with a higher and more diverse number of significant determinants of forest cover. Additionally, we detected stronger spatial interactions at smaller levels, providing empirical evidence that certain deforestation forces occur independently of the existing de jure governance boundaries. We demonstrated that neglecting spatial dependencies in this type of studies can lead to several misinterpretations. We therefore advocate, that the design and enforcement of policy instruments-such as REDD+-should start from common international entry points that ensure for coherent agricultural and demographic policies. In order to achieve a long-term impact on the ground, these policies need to have enough flexibility to be modified and adapted to specific national, regional or local conditions.

Understanding the Spatial Agglomeration of Participation in Agri-Environmental Schemes: The Case of the Tuscany Region

Agri-environmental schemes (AESs) constitute one of the main agricultural policy instruments that address environmental objectives in the Common Agricultural Policy. However, in spite of a 20-year application window and large budgetary shares allocated by EU member states, several studies demonstrate lower-than-expected environmental impacts. The reasons for poor environmental outcomes are the lack of targeting, low participation rates, spatial heterogeneity, and information asymmetry between farmers and public administrators. This study comprehensively analyses the determinants of AES adoption while highlighting patterns of the spatial agglomeration of participation in organic and integrated production. For this, we combine the results of farm-level adoption analysis with a spatial analysis of the participation rate. The results show that both micro- and meso-level characteristics strongly impact AES participation. In fact, farm and household structure, quality of extension services, and territorial conditions all significantly affect AES adoption.

The Role of Factors Affecting the Adoption of Environmentally Friendly Farming Practices: Can Geographical Context and Time Explain the Differences Emerging from Literature?

Environmentally Friendly Farming Practices (EFFPs) are tools aimed at providing ecosystem services or mitigating the environmental impacts of intensive agriculture. A large literature has explored the factors affecting the adoption of EFFPs by farmers. However, opposite effects of several factors on uptake have often emerged. We carried out a qualitative meta-analysis of the literature seeking to identify some geographical and temporal trends that can provide a rationale to explain these opposite results. To reach this goal, we analysed the literature and classified the following factors affecting farmers’ behaviour according to the theory of reasoned action and planned behaviour: farm, farmer, informational, and social factors. Our perspective in exploring the existing literature shows that the geographical context and the temporal period under analysis, considered as different adopters’ cohorts, can explain most of the opposite effects. For example, while the different effects of farm structural factors show specific geographical patterns, those of the management and economic factors follow temporal trends. The impact of some farmers’ socio-demographical characteristics and some social factors can be explained in terms of both geographical context and time. The broad trends we found cast light on the importance of further research adopting the same methodological approach in different geographical contexts and under a temporal perspective.

The Use of Spatial Econometrics, Stakeholder Analysis and Qualitative Methodologies in The Evaluation of Rural Development Policy

The analysis and evaluation of European Rural Development Policy (RDP) is challenging because of its delivery at multiple scales by multiple actors. To address this challenge the Common Monitoring and Evaluation Framework (CMEF) indicators were introduced. However, these quantitative indicators are limited by data gaps and their inability to address the less tangible aspects of policy performance. In this paper we explore, how to address these limitations through complimentary policy evaluation approaches using evidence from empirical studies. We discuss the strengths and weakness of applying three different quantitative and qualitative evaluation approaches: (1) spatial econometrics; (2) stakeholder analysis; and, (3) qualitative interviews. The findings from the three methods are then triangulated proposing the potential of an integrated methodological approach to inform policy and management. A mixed method approach provides a broader understanding of how policy design, stakeholder's roles, and spatial characteristics impact on implementation and environmental targeting capacity, highlighting the multifaceted nature of the determinants of policy performance.